1. Field of the Invention
The present invention generally relates to the field of telecommunications, and more specifically to methods and systems for the simulation of radio telecommunication networks like cellular and wireless networks. In particular, the simulation of the physical level of a radio network is considered.
2. Discussion of the Related Art
In the field of telecommunications and, in particular, of radio telecommunication networks like cellular networks (e.g., mobile telephony networks) and wireless networks (e.g., WiMax networks), simulation tools are for example used to define the network architecture before the deployment, and, after the network deployment, to assess the network compliance with desired traffic/service handling capabilities, in order for example to upgrade the already deployed network.
Radio telecommunication networks are complex systems that cannot in general be analytically modeled by means of mathematical equations.
Two approaches are known in the art for simulating the behavior of a complex system like a radio network: a dynamic approach and a static, or “MonteCarlo” approach.
In the dynamic approach, the evolution in time of the system is taken into consideration, and the changes of state of the system occur as a consequence of events. The generic event represents the occurrence of a condition that causes the system state to change. By performing a simulation that takes into consideration the evolution of the system state over a certain time period, it is possible to gain an overall evaluation of the system behavior.
In the static approach, the evolution in time is not considered, and the analysis is conducted in respect of a certain condition of the system; in other words, a snapshot of the system at a certain time instant is taken. An overall evaluation of the system behavior can in this case be gained by taking different snapshots of the system, at different time instants.
Dynamic simulators are generally significantly more complex than MonteCarlo simulators, thus MonteCarlo simulations take less time and need less computing resources.
Both dynamic and static approaches can be used to simulate radio telecommunication networks, the choice depending on the type of analysis which is desired to be performed. If the interest is on the network parameters that are related to time, like for example the time required to set up a call, dynamic simulations are conducted; if instead the interest is on network parameters that are not related to time, e.g. the interferential state experienced at a receiver, albeit dynamic simulations might in principle be used, static simulations are preferred because they are faster.
As discussed in the Dissertation for the degree of Doctor of Technology presented by H. Holma entitled “A STUDY OF UMTS TERRESTRIAL RADIO ACCESS PERFORMANCE”, presented at Helsinki University of Technology (Espoo, Finland) on the 24th of Oct., 2003, pages 23-30 the simulators for cellular and wireless networks can be classified as belonging to two broad families: link-level simulators and system-level simulators. Link-level simulators consider a single radio link between the transmitter and the receiver, and analyze in detail the physical-level performance of the considered transmission system. System-level simulators analyze the behavior of a set of base radio stations of the network and of user terminals in a considered geographic area, and take into consideration phenomena like the traffic, the interferential situation and the radio resources management.
Typically, system-level simulators exploit models of the physical level of the system to be simulated which are based on the results obtained by running link-level simulators. As discussed in the cited Dissertation by Holma, and in S. Hämäläinen, H. Holma, K. Sipilä “ADVANCED WCDMA RADIO NETWORK SIMULATOR”, PIMRC'99—Osaka, Japan, 12-15 Sep. 1999, pages 951-955, link-level simulators may for example provide, as a result of the simulation, curves that give a relation between the physical-level performance and the estimated interferential conditions experienced; the considered performance may relate to the data loss rate (e.g., the BLER—BLock Erasure Rate—or the FER—Frame Error Rate—or the PER—Packet Error Rate) as a function of the SNR (Signal to Noise Ratio, which may be expressed as Eb/N0, the ratio of the energy per bit to noise power spectral density). Other examples are provided in N. Souto et al., “UMTS AWGN Simulation Results for Uplink, Downlink and HSDPA transmissions” Mobile Communications Summit, Aveiro, Portugal, June, 2003, Vol. 1, pages 543-547.
System-level simulators model the transmission of multiple data packets; as discussed in D. Molkdar, W. Featherstone, “System level performance evaluation of EGPRS in GSM macro-cellular environments” VTC 2000, pages 2653-2660, for each transmission the following check is performed: the SNR, or Eb/N0, is calculated; using a curve obtained by running a link-level simulator, the average loss rate is determined which corresponds to a measured SNR or Eb/No value; a random number with uniform distribution between 0 and 1 is extracted, and if such a random number is less than the average loss rate determined above, the data packet is considered lost, otherwise it is considered correctly received.
US 2007/036088 discloses simulation models of media access control and physical layer characteristics that facilitate the simulation/emulation of a variety of phenomena that affect transmissions via a wireless media. Such phenomena include media access contention delays, packet drops, and retransmissions that are generally dependent upon changes in transmitter/receiver locations. Each wireless environment is characterized by a model of the communication channel that characterizes transmission effects based on the number of competing transmitters in the environment, which is dynamically determined based on the location of each node in the environment. Additionally, the location of nodes is used to simulate the effects of ‘hidden nodes’, nodes that are unknown to a transmitting node but can interfere with the reception of transmissions at a receiving node. Each device/node model in the wireless environment preferably accesses the same model of the communication channel, thereby minimizing the amount of detail required at each device model.